Data-driven control of flapping flight

Abstract

We present a physically based controller that simulates the flapping behavior of a bird in flight. We recorded the motion of a dove using marker-based optical motion capture and high-speed video cameras. The bird flight data thus acquired allow us to parameterize natural wingbeat cycles and provide the simulated bird with reference trajectories to track in physics simulation. Our controller simulates articulated rigid bodies of a bird's skeleton and deformable feathers to reproduce the aerodynamics of bird flight. Motion capture from live birds is not as easy as human motion capture because of the lack of cooperation from subjects. Therefore, the flight data we could acquire were limited. We developed a new method to learn wingbeat controllers even from sparse, biased observations of real bird flight. Our simulated bird imitates life-like flapping of a flying bird while actively maintaining its balance. The bird flight is interactively controllable and resilient to external disturbances.